A novel technique for automatic shoeprint image retrieval

被引：44

作者：

AlGarni, Gharsa ^{[2
]}

Hamiane, Madina ^{[1
]}

机构：

[1] Royal Univ Women, W Riffa, Bahrain

[2] Dammam Girls Coll Sci, Dammam, Saudi Arabia

来源：

FORENSIC SCIENCE INTERNATIONAL | 2008年 / 181卷 / 1-3期

关键词：

Shoeprint classification; Feature extraction; Content Based Image Retrieval (CBIR); Hu's seven moment invariants; Forensics; Distance measure;

D O I：

10.1016/j.forsciint.2008.07.004

中图分类号：

DF [法律]; D9 [法律]; R [医药、卫生];

学科分类号：

0301 ; 10 ;

摘要：

Recent developments in forensic science have resulted in large numbers of scene of crime images being collected for recording and analysis. Shoeprint images are no exception. In fact, these have recently been of great interest to police and forensic scientists as footwear evidence is now treated in the same manner as fingerprint and DNA evidence. Traditional approaches to shoeprint representations attempt to classify shoeprint images based on a number of possible patterns. Such approaches are difficult to implement in an automatic fashion without the intervention of a forensic specialist. This paper presents a robust algorithm for shoeprint matching based on Hu's moment invariants. It is shown that decreasing the resolution of images does not have a significant effect on the performance of the algorithm. It is also shown that the Optimal Performance of the proposed system is attained for images rotated by any angle. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

引用

页码：10 / 14

页数：5

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